init - 初始化项目

samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp

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+/**
+ * @file Sobel_Demo.cpp
+ * @brief Sample code uses Sobel or Scharr OpenCV functions for edge detection
+ * @author OpenCV team
+ */
+
+#include "opencv2/imgproc.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/highgui.hpp"
+
+#include <iostream>
+
+using namespace cv;
+using namespace std;
+
+/**
+ * @function main
+ */
+int main( int argc, char** argv )
+{
+  cv::CommandLineParser parser(argc, argv,
+                               "{@input   |lena.jpg|input image}"
+                               "{ksize   k|1|ksize (hit 'K' to increase its value at run time)}"
+                               "{scale   s|1|scale (hit 'S' to increase its value at run time)}"
+                               "{delta   d|0|delta (hit 'D' to increase its value at run time)}"
+                               "{help    h|false|show help message}");
+
+  cout << "The sample uses Sobel or Scharr OpenCV functions for edge detection\n\n";
+  parser.printMessage();
+  cout << "\nPress 'ESC' to exit program.\nPress 'R' to reset values ( ksize will be -1 equal to Scharr function )";
+
+  //![variables]
+  // First we declare the variables we are going to use
+  Mat image,src, src_gray;
+  Mat grad;
+  const String window_name = "Sobel Demo - Simple Edge Detector";
+  int ksize = parser.get<int>("ksize");
+  int scale = parser.get<int>("scale");
+  int delta = parser.get<int>("delta");
+  int ddepth = CV_16S;
+  //![variables]
+
+  //![load]
+  String imageName = parser.get<String>("@input");
+  // As usual we load our source image (src)
+  image = imread( samples::findFile( imageName ), IMREAD_COLOR ); // Load an image
+
+  // Check if image is loaded fine
+  if( image.empty() )
+  {
+    printf("Error opening image: %s\n", imageName.c_str());
+    return EXIT_FAILURE;
+  }
+  //![load]
+
+  for (;;)
+  {
+    //![reduce_noise]
+    // Remove noise by blurring with a Gaussian filter ( kernel size = 3 )
+    GaussianBlur(image, src, Size(3, 3), 0, 0, BORDER_DEFAULT);
+    //![reduce_noise]
+
+    //![convert_to_gray]
+    // Convert the image to grayscale
+    cvtColor(src, src_gray, COLOR_BGR2GRAY);
+    //![convert_to_gray]
+
+    //![sobel]
+    /// Generate grad_x and grad_y
+    Mat grad_x, grad_y;
+    Mat abs_grad_x, abs_grad_y;
+
+    /// Gradient X
+    Sobel(src_gray, grad_x, ddepth, 1, 0, ksize, scale, delta, BORDER_DEFAULT);
+
+    /// Gradient Y
+    Sobel(src_gray, grad_y, ddepth, 0, 1, ksize, scale, delta, BORDER_DEFAULT);
+    //![sobel]
+
+    //![convert]
+    // converting back to CV_8U
+    convertScaleAbs(grad_x, abs_grad_x);
+    convertScaleAbs(grad_y, abs_grad_y);
+    //![convert]
+
+    //![blend]
+    /// Total Gradient (approximate)
+    addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);
+    //![blend]
+
+    //![display]
+    imshow(window_name, grad);
+    char key = (char)waitKey(0);
+    //![display]
+
+    if(key == 27)
+    {
+      return EXIT_SUCCESS;
+    }
+
+    if (key == 'k' || key == 'K')
+    {
+      ksize = ksize < 30 ? ksize+2 : -1;
+    }
+
+    if (key == 's' || key == 'S')
+    {
+      scale++;
+    }
+
+    if (key == 'd' || key == 'D')
+    {
+      delta++;
+    }
+
+    if (key == 'r' || key == 'R')
+    {
+      scale =  1;
+      ksize = -1;
+      delta =  0;
+    }
+  }
+  return EXIT_SUCCESS;
+}